Overview

Dataset statistics

Number of variables11
Number of observations250
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.6 KiB
Average record size in memory88.5 B

Variable types

NUM11

Reproduction

Analysis started2020-08-25 00:32:47.184905
Analysis finished2020-08-25 00:33:03.944793
Duration16.76 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

oz5 is highly correlated with oz3High correlation
oz3 is highly correlated with oz5High correlation
oz1 has unique values Unique
oz2 has unique values Unique
oz3 has unique values Unique
oz4 has unique values Unique
oz5 has unique values Unique
oz6 has unique values Unique
oz7 has unique values Unique
oz8 has unique values Unique
oz9 has unique values Unique
oz10 has unique values Unique
target has unique values Unique

Variables

oz1
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.434717655181885e-09
Minimum-2.4286046028137207
Maximum2.118593692779541
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:03.990556image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.428604603
5-th percentile-1.657227451
Q1-0.6812887788
median-0.06594005413
Q30.7720926553
95-th percentile1.667501742
Maximum2.118593693
Range4.547198296
Interquartile range (IQR)1.453381434

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)-291144746.6
Kurtosis-0.7255971278
Mean-3.434717655e-09
Median Absolute Deviation (MAD)0.7329620719
Skewness0.001730700047
Sum-8.586794138e-07
Variance1.000000002
2020-08-25T00:33:04.087720image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.72069239610.4%
 
-1.88801753510.4%
 
-1.45057070310.4%
 
0.420991182310.4%
 
0.969909727610.4%
 
-0.555845141410.4%
 
0.472990423410.4%
 
2.06367683410.4%
 
0.150677874710.4%
 
-0.347326517110.4%
 
-0.0704160258210.4%
 
1.3558033710.4%
 
1.08811664610.4%
 
1.68532216510.4%
 
-0.350667089210.4%
 
2.01477336910.4%
 
0.42926144610.4%
 
1.68035435710.4%
 
0.252550303910.4%
 
-0.174632325810.4%
 
1.49638938910.4%
 
-0.466512471410.4%
 
-0.439383059710.4%
 
0.209256082810.4%
 
-0.173514738710.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-2.42860460310.4%
 
-2.03163981410.4%
 
-1.88801753510.4%
 
-1.88155758410.4%
 
-1.85177040110.4%
 
-1.81765019910.4%
 
-1.81275558510.4%
 
-1.80422580210.4%
 
-1.7487516410.4%
 
-1.7334282410.4%
 
ValueCountFrequency (%) 
2.11859369310.4%
 
2.06367683410.4%
 
2.01477336910.4%
 
1.99400174610.4%
 
1.98587429510.4%
 
1.90971374510.4%
 
1.89335024410.4%
 
1.78342914610.4%
 
1.72069239610.4%
 
1.70603573310.4%
 

oz2
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.7136335372924804e-10
Minimum-1.7072352170944214
Maximum1.6689813137054443
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:04.194801image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.707235217
5-th percentile-1.53767131
Q1-0.8958309293
median-0.005190636031
Q30.907957077
95-th percentile1.518771279
Maximum1.668981314
Range3.376216531
Interquartile range (IQR)1.803788006

Descriptive statistics

Standard deviation0.9999999981
Coefficient of variation (CV)-5835553380
Kurtosis-1.191059815
Mean-1.713633537e-10
Median Absolute Deviation (MAD)0.8923615264
Skewness-0.006975877685
Sum-4.284083843e-08
Variance0.9999999962
2020-08-25T00:33:04.305446image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.381590366410.4%
 
0.165084004410.4%
 
1.50235259510.4%
 
1.06094348410.4%
 
-0.477929890210.4%
 
1.40684068210.4%
 
-0.166551992310.4%
 
1.62440657610.4%
 
-0.7287033210.4%
 
-0.412202209210.4%
 
0.924502611210.4%
 
-0.56846219310.4%
 
0.0335501544210.4%
 
-1.43981385210.4%
 
-0.893242776410.4%
 
0.217448726310.4%
 
-1.40847945210.4%
 
0.61686140310.4%
 
0.315011471510.4%
 
0.474446207310.4%
 
0.644199669410.4%
 
-0.0688060745610.4%
 
-0.584622144710.4%
 
-1.38251578810.4%
 
0.560693323610.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.70723521710.4%
 
-1.69128239210.4%
 
-1.69064080710.4%
 
-1.68511140310.4%
 
-1.67839205310.4%
 
-1.67671406310.4%
 
-1.65918350210.4%
 
-1.658083210.4%
 
-1.63653576410.4%
 
-1.62760639210.4%
 
ValueCountFrequency (%) 
1.66898131410.4%
 
1.66023576310.4%
 
1.65154719410.4%
 
1.65108764210.4%
 
1.64697289510.4%
 
1.62947225610.4%
 
1.62440657610.4%
 
1.59364306910.4%
 
1.59298074210.4%
 
1.57531845610.4%
 

oz3
Real number (ℝ)

HIGH CORRELATION
UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.0728836059570312e-09
Minimum-1.9171030521392824
Maximum2.7800800800323486
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:04.420202image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.917103052
5-th percentile-1.286448032
Q1-0.7012441158
median-0.2699349523
Q30.5908212066
95-th percentile1.880401534
Maximum2.78008008
Range4.697183132
Interquartile range (IQR)1.292065322

Descriptive statistics

Standard deviation1.000000002
Coefficient of variation (CV)-932067557.8
Kurtosis0.1218918789
Mean-1.072883606e-09
Median Absolute Deviation (MAD)0.5933224261
Skewness0.7699137295
Sum-2.682209015e-07
Variance1.000000005
2020-08-25T00:33:04.521116image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.90212833910.4%
 
-0.120259523410.4%
 
0.395903706610.4%
 
-1.33142089810.4%
 
2.52025318110.4%
 
0.209273204210.4%
 
-0.405118763410.4%
 
-0.448329687110.4%
 
-0.11184267710.4%
 
-0.408605098710.4%
 
-0.844410002210.4%
 
-0.894702196110.4%
 
-0.790697932210.4%
 
-1.67662084110.4%
 
1.8538465510.4%
 
-0.690589308710.4%
 
0.994009494810.4%
 
-0.663732528710.4%
 
0.185457333910.4%
 
-0.210165888110.4%
 
-0.0268059447410.4%
 
1.26983451810.4%
 
-0.832670748210.4%
 
-0.619778811910.4%
 
-0.549353480310.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.91710305210.4%
 
-1.85822045810.4%
 
-1.67682421210.4%
 
-1.67662084110.4%
 
-1.67395579810.4%
 
-1.57485413610.4%
 
-1.50168287810.4%
 
-1.46781396910.4%
 
-1.36191749610.4%
 
-1.35671651410.4%
 
ValueCountFrequency (%) 
2.7800800810.4%
 
2.77815079710.4%
 
2.72605752910.4%
 
2.67687201510.4%
 
2.6436357510.4%
 
2.57301068310.4%
 
2.52025318110.4%
 
2.31157541310.4%
 
2.30607581110.4%
 
2.19251632710.4%
 

oz4
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.4994293451309205e-09
Minimum-1.6518397331237793
Maximum1.6098575592041016
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:04.631677image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.651839733
5-th percentile-1.549919313
Q1-0.9049836695
median0.04596606083
Q30.898381561
95-th percentile1.541568434
Maximum1.609857559
Range3.261697292
Interquartile range (IQR)1.803365231

Descriptive statistics

Standard deviation0.9999999942
Coefficient of variation (CV)-666920383.7
Kurtosis-1.290883216
Mean-1.499429345e-09
Median Absolute Deviation (MAD)0.9138779044
Skewness0.001576376872
Sum-3.748573363e-07
Variance0.9999999885
2020-08-25T00:33:04.739532image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1.46313166610.4%
 
-0.772137999510.4%
 
-1.54969632610.4%
 
1.27966690110.4%
 
1.57827734910.4%
 
-0.242110773910.4%
 
-0.906069576710.4%
 
1.55407118810.4%
 
1.29332697410.4%
 
-1.29625415810.4%
 
-1.58360958110.4%
 
0.495302885810.4%
 
0.663749456410.4%
 
-0.998284280310.4%
 
0.0385753624110.4%
 
-0.662316381910.4%
 
1.58718204510.4%
 
-0.97281998410.4%
 
0.350422918810.4%
 
-0.440509796110.4%
 
-1.28254318210.4%
 
-0.484135806610.4%
 
1.47296595610.4%
 
-1.5520672810.4%
 
-0.0439662300110.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.65183973310.4%
 
-1.62752497210.4%
 
-1.62322652310.4%
 
-1.61779105710.4%
 
-1.59535837210.4%
 
-1.58360958110.4%
 
-1.56683385410.4%
 
-1.5591605910.4%
 
-1.55649912410.4%
 
-1.5525089510.4%
 
ValueCountFrequency (%) 
1.60985755910.4%
 
1.60916042310.4%
 
1.60337960710.4%
 
1.59853160410.4%
 
1.58718204510.4%
 
1.57827734910.4%
 
1.57496786110.4%
 
1.57064592810.4%
 
1.5584791910.4%
 
1.55770218410.4%
 

oz5
Real number (ℝ)

HIGH CORRELATION
UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.2258609533309938e-09
Minimum-1.501611828804016
Maximum3.9639952182769775
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:04.859774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.501611829
5-th percentile-1.001247478
Q1-0.7051306665
median-0.3487244695
Q30.518714875
95-th percentile2.175535679
Maximum3.963995218
Range5.465607047
Interquartile range (IQR)1.223845541

Descriptive statistics

Standard deviation0.9999999987
Coefficient of variation (CV)-449264360.9
Kurtosis2.121880177
Mean-2.225860953e-09
Median Absolute Deviation (MAD)0.4533940144
Skewness1.451888849
Sum-5.564652383e-07
Variance0.9999999975
2020-08-25T00:33:04.965540image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1.10351920110.4%
 
-0.183388635510.4%
 
-0.675955414810.4%
 
-0.858083248110.4%
 
-0.507496118510.4%
 
-1.50161182910.4%
 
-0.558761656310.4%
 
2.32550668710.4%
 
-0.470785349610.4%
 
-0.905925989210.4%
 
-0.171305552110.4%
 
1.68587243610.4%
 
-0.813232183510.4%
 
0.087524950510.4%
 
-0.230752438310.4%
 
0.120098277910.4%
 
-0.609011769310.4%
 
0.102008499210.4%
 
-1.01644718610.4%
 
-0.512587308910.4%
 
-0.0115989167210.4%
 
-0.425120145110.4%
 
-0.0990777239210.4%
 
-0.681780934310.4%
 
-0.861955285110.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.50161182910.4%
 
-1.44795215110.4%
 
-1.35884094210.4%
 
-1.33782410610.4%
 
-1.15847551810.4%
 
-1.13233804710.4%
 
-1.10351920110.4%
 
-1.10130929910.4%
 
-1.0327154410.4%
 
-1.03008711310.4%
 
ValueCountFrequency (%) 
3.96399521810.4%
 
3.73543477110.4%
 
3.59427475910.4%
 
3.51828646710.4%
 
2.44848108310.4%
 
2.37838435210.4%
 
2.36117482210.4%
 
2.33147168210.4%
 
2.32550668710.4%
 
2.32038283310.4%
 

oz6
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.848705768585205e-10
Minimum-2.2720327377319336
Maximum2.807206630706787
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:05.074694image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.272032738
5-th percentile-1.264066434
Q1-0.7904641181
median-0.2351881862
Q30.6233696193
95-th percentile1.830995399
Maximum2.807206631
Range5.079239368
Interquartile range (IQR)1.413833737

Descriptive statistics

Standard deviation1.000000002
Coefficient of variation (CV)1709779978
Kurtosis0.06053719483
Mean5.848705769e-10
Median Absolute Deviation (MAD)0.6439907849
Skewness0.7629423308
Sum1.462176442e-07
Variance1.000000005
2020-08-25T00:33:05.177782image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1.10253310210.4%
 
-0.163122251610.4%
 
-1.15466105910.4%
 
0.969546973710.4%
 
-0.502617359210.4%
 
-1.31089794610.4%
 
-0.481041431410.4%
 
0.227703079610.4%
 
-0.815595030810.4%
 
0.539712250210.4%
 
-0.066274680210.4%
 
-0.260575532910.4%
 
-0.411789834510.4%
 
0.251538932310.4%
 
2.33066797310.4%
 
-0.653951764110.4%
 
-1.28834021110.4%
 
0.476333349910.4%
 
2.80720663110.4%
 
0.823848247510.4%
 
0.934706211110.4%
 
1.63796663310.4%
 
0.204379379710.4%
 
-0.466459333910.4%
 
0.444646775710.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-2.27203273810.4%
 
-1.88182759310.4%
 
-1.45545256110.4%
 
-1.42672336110.4%
 
-1.38936603110.4%
 
-1.36568224410.4%
 
-1.33113539210.4%
 
-1.32617664310.4%
 
-1.31089794610.4%
 
-1.31048464810.4%
 
ValueCountFrequency (%) 
2.80720663110.4%
 
2.80365729310.4%
 
2.64885449410.4%
 
2.6206097610.4%
 
2.55322527910.4%
 
2.46294426910.4%
 
2.41281628610.4%
 
2.33455061910.4%
 
2.33066797310.4%
 
2.28873443610.4%
 

oz7
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.896413207054138e-09
Minimum-1.5660804510116575
Maximum1.88345205783844
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:05.448313image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.566080451
5-th percentile-1.437578553
Q1-0.8006329089
median-0.1212036386
Q30.7919240892
95-th percentile1.715402216
Maximum1.883452058
Range3.449532509
Interquartile range (IQR)1.592556998

Descriptive statistics

Standard deviation0.9999999995
Coefficient of variation (CV)-345254605.6
Kurtosis-1.121785856
Mean-2.896413207e-09
Median Absolute Deviation (MAD)0.8171505406
Skewness0.2434012663
Sum-7.241033018e-07
Variance0.9999999989
2020-08-25T00:33:05.551638image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.576117992410.4%
 
-0.88392829910.4%
 
-0.755542218710.4%
 
-1.48390507710.4%
 
0.198734775210.4%
 
0.983075857210.4%
 
-0.621257543610.4%
 
-1.56608045110.4%
 
1.30989134310.4%
 
-1.03743314710.4%
 
1.47492814110.4%
 
-0.784826040310.4%
 
-0.647616922910.4%
 
-0.419265091410.4%
 
1.67022144810.4%
 
-0.597493290910.4%
 
0.124740809210.4%
 
1.44267082210.4%
 
-0.614400684810.4%
 
0.620258986910.4%
 
-1.25516426610.4%
 
-1.09402954610.4%
 
1.35085868810.4%
 
-1.27859258710.4%
 
0.394598692710.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.56608045110.4%
 
-1.56399071210.4%
 
-1.54446065410.4%
 
-1.53595495210.4%
 
-1.51664423910.4%
 
-1.51395678510.4%
 
-1.50999784510.4%
 
-1.50847685310.4%
 
-1.48791575410.4%
 
-1.48390507710.4%
 
ValueCountFrequency (%) 
1.88345205810.4%
 
1.87846493710.4%
 
1.86763668110.4%
 
1.86121785610.4%
 
1.8331122410.4%
 
1.80055534810.4%
 
1.79204368610.4%
 
1.78519320510.4%
 
1.75515294110.4%
 
1.74836635610.4%
 

oz8
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.074566721916199e-10
Minimum-1.8097778558731081
Maximum1.6599233150482178
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:05.670330image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.809777856
5-th percentile-1.64614116
Q1-0.8283576369
median0.1055177115
Q30.8152116239
95-th percentile1.473388743
Maximum1.659923315
Range3.469701171
Interquartile range (IQR)1.643569261

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)-1238456546
Kurtosis-1.155387527
Mean-8.074566722e-10
Median Absolute Deviation (MAD)0.833997488
Skewness-0.1987434308
Sum-2.01864168e-07
Variance1.000000002
2020-08-25T00:33:05.774297image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.850585281810.4%
 
-1.53840911410.4%
 
0.749203145510.4%
 
0.936345934910.4%
 
1.64878976310.4%
 
0.106423400310.4%
 
-0.450282514110.4%
 
1.47495257910.4%
 
-1.33725357110.4%
 
-1.1637399210.4%
 
0.442954152810.4%
 
0.83170831210.4%
 
-1.16634631210.4%
 
0.380452543510.4%
 
-0.318930536510.4%
 
-1.80045926610.4%
 
1.11646723710.4%
 
-1.64680194910.4%
 
-0.430498242410.4%
 
-0.593904554810.4%
 
1.49381101110.4%
 
-1.65167343610.4%
 
-0.349012762310.4%
 
-1.09208035510.4%
 
-0.109819792210.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.80977785610.4%
 
-1.80045926610.4%
 
-1.78859841810.4%
 
-1.76876485310.4%
 
-1.75735425910.4%
 
-1.73871946310.4%
 
-1.72796201710.4%
 
-1.71166241210.4%
 
-1.69138002410.4%
 
-1.67632234110.4%
 
ValueCountFrequency (%) 
1.65992331510.4%
 
1.65801060210.4%
 
1.64878976310.4%
 
1.63555705510.4%
 
1.62628984510.4%
 
1.5930098310.4%
 
1.56307077410.4%
 
1.55780005510.4%
 
1.54557335410.4%
 
1.5073405510.4%
 

oz9
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-7.809139788150788e-10
Minimum-1.8667882680892944
Maximum1.7703254222869873
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:05.887964image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.866788268
5-th percentile-1.614347827
Q1-0.8496487141
median-0.01094124169
Q30.8133038729
95-th percentile1.609730309
Maximum1.770325422
Range3.63711369
Interquartile range (IQR)1.662952587

Descriptive statistics

Standard deviation0.9999999982
Coefficient of variation (CV)-1280550772
Kurtosis-1.059262347
Mean-7.809139788e-10
Median Absolute Deviation (MAD)0.8357912302
Skewness-0.03775700497
Sum-1.952284947e-07
Variance0.9999999964
2020-08-25T00:33:05.991383image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-1.19531071210.4%
 
-1.24557006410.4%
 
0.445155143710.4%
 
1.33335304310.4%
 
0.0261741988410.4%
 
1.61752939210.4%
 
1.51721954310.4%
 
0.68278521310.4%
 
-0.206706941110.4%
 
-1.47591900810.4%
 
1.05165350410.4%
 
1.29134380810.4%
 
0.561928987510.4%
 
0.552947282810.4%
 
-1.61554849110.4%
 
-1.05047392810.4%
 
0.080947540710.4%
 
0.589017450810.4%
 
-0.851707935310.4%
 
-1.01298403710.4%
 
-0.0930772125710.4%
 
-1.61018717310.4%
 
1.61468064810.4%
 
-0.125400364410.4%
 
-1.54324054710.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.86678826810.4%
 
-1.86607158210.4%
 
-1.85822832610.4%
 
-1.85493886510.4%
 
-1.81569969710.4%
 
-1.80078160810.4%
 
-1.76488363710.4%
 
-1.75638985610.4%
 
-1.74290382910.4%
 
-1.73252344110.4%
 
ValueCountFrequency (%) 
1.77032542210.4%
 
1.76225709910.4%
 
1.75312852910.4%
 
1.71718835810.4%
 
1.70810747110.4%
 
1.70239925410.4%
 
1.70205330810.4%
 
1.68430364110.4%
 
1.64619028610.4%
 
1.62877678910.4%
 

oz10
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3504177331924438e-10
Minimum-1.7008146047592163
Maximum1.7285373210906982
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:06.109831image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-1.700814605
5-th percentile-1.554691559
Q1-0.8467017412
median-0.04140343517
Q30.8273483664
95-th percentile1.600040841
Maximum1.728537321
Range3.429351926
Interquartile range (IQR)1.674050108

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)7405116031
Kurtosis-1.145872044
Mean1.350417733e-10
Median Absolute Deviation (MAD)0.8502214551
Skewness0.0003570503809
Sum3.376044333e-08
Variance1.000000001
2020-08-25T00:33:06.213895image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
-0.350096613210.4%
 
-1.69795119810.4%
 
-1.07846903810.4%
 
-1.57455980810.4%
 
1.19271814810.4%
 
1.18978655310.4%
 
-0.0356164090310.4%
 
-0.0471904613110.4%
 
-1.11799371210.4%
 
1.72493314710.4%
 
-0.617346823210.4%
 
-1.13605940310.4%
 
-1.30792224410.4%
 
-0.378735780710.4%
 
1.11005866510.4%
 
-1.33915293210.4%
 
1.07444155210.4%
 
-1.50321483610.4%
 
1.52762544210.4%
 
1.030972610.4%
 
-1.70081460510.4%
 
-1.22487497310.4%
 
1.20314192810.4%
 
0.913583219110.4%
 
-0.515754342110.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-1.70081460510.4%
 
-1.69962215410.4%
 
-1.69795119810.4%
 
-1.68169641510.4%
 
-1.67299175310.4%
 
-1.66784584510.4%
 
-1.62770640910.4%
 
-1.60190737210.4%
 
-1.59531903310.4%
 
-1.57455980810.4%
 
ValueCountFrequency (%) 
1.72853732110.4%
 
1.72493314710.4%
 
1.7045919910.4%
 
1.69129061710.4%
 
1.68643629610.4%
 
1.68044996310.4%
 
1.66029226810.4%
 
1.6587059510.4%
 
1.65328991410.4%
 
1.6264126310.4%
 

target
Real number (ℝ)

UNIQUE

Distinct count250
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.881752490997315e-09
Minimum-2.484710216522217
Maximum3.3784804344177246
Zeros0
Zeros (%)0.0%
Memory size2.1 KiB
2020-08-25T00:33:06.329806image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum-2.484710217
5-th percentile-1.761403257
Q1-0.565447852
median0.0706185177
Q30.5665611327
95-th percentile1.499455673
Maximum3.378480434
Range5.863190651
Interquartile range (IQR)1.132008985

Descriptive statistics

Standard deviation1.000000001
Coefficient of variation (CV)257615601.1
Kurtosis1.021173614
Mean3.881752491e-09
Median Absolute Deviation (MAD)0.5651633367
Skewness0.1438361961
Sum9.704381227e-07
Variance1.000000002
2020-08-25T00:33:06.433071image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.695312082810.4%
 
-0.369954079410.4%
 
0.0671419799310.4%
 
0.25253266110.4%
 
-0.238204613310.4%
 
0.511240124710.4%
 
-0.165360674310.4%
 
0.665701568110.4%
 
0.852223038710.4%
 
-0.747727155710.4%
 
-1.70834243310.4%
 
-1.32259929210.4%
 
0.223308041710.4%
 
0.808269083510.4%
 
-1.54849743810.4%
 
0.45491349710.4%
 
0.48761713510.4%
 
0.267901688810.4%
 
0.091472208510.4%
 
1.62041163410.4%
 
-1.156551610.4%
 
0.528471350710.4%
 
0.430983424210.4%
 
-0.799464404610.4%
 
-2.08847999610.4%
 
Other values (225)22590.0%
 
ValueCountFrequency (%) 
-2.48471021710.4%
 
-2.38725304610.4%
 
-2.22202229510.4%
 
-2.1078417310.4%
 
-2.08847999610.4%
 
-2.07548785210.4%
 
-2.01394367210.4%
 
-2.01190400110.4%
 
-2.00251650810.4%
 
-1.98751294610.4%
 
ValueCountFrequency (%) 
3.37848043410.4%
 
3.32224845910.4%
 
3.28686475810.4%
 
3.28515195810.4%
 
1.90973067310.4%
 
1.86242866510.4%
 
1.84161901510.4%
 
1.71787238110.4%
 
1.6849415310.4%
 
1.62041163410.4%
 

Interactions

2020-08-25T00:32:47.629884image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:47.738466image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:47.855587image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:47.978082image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.095791image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.207757image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.318877image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.439379image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.558551image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.694391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.810751image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:48.923059image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.045905image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.173165image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.295970image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.422989image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.546157image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.672669image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.804555image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:49.931497image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.063695image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.360976image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.482947image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.597980image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.724934image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.840707image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:50.966898image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.086248image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.205502image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.329936image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.450526image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.585436image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.706747image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.823791image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:51.943699image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.072382image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.196499image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.324918image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.447215image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.571496image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.703202image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.838592image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:52.971913image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.100488image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.223907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.337111image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.458296image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.577915image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.705317image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.821121image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:53.936977image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.225712image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.348443image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.477127image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.599001image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.719310image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.840128image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:54.960372image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.076152image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.197871image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.312096image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.427567image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.552510image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.674610image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.799530image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:55.920429image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.036307image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.161542image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.294705image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.423068image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.556135image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.683705image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.810250image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:56.967155image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:57.151509image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:57.324460image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:57.465963image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:57.594096image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:57.715210image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:57.842850image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.126912image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.256297image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.378489image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.500376image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.631447image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.762256image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:58.893762image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.021038image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.143907image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.270344image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.402757image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.533303image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.665562image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.793904image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:32:59.921174image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.057235image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.192288image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.328519image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.459908image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.587948image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.706170image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.832669image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:00.954522image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:01.082387image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:01.206470image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:01.330347image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:01.461734image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:01.587547image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:01.720014image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.014777image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.136783image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.250090image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.371835image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.488014image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.609687image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.727549image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.846843image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:02.975128image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:03.097336image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:03.224906image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:03.347450image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T00:33:06.566428image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T00:33:06.792499image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T00:33:07.017749image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T00:33:07.240129image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T00:33:03.575335image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:33:03.845132image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

oz1oz2oz3oz4oz5oz6oz7oz8oz9oz10target
0-0.531625-0.1665520.7107571.472966-0.188466-1.018317-1.393816-1.0415690.4885400.1561591.332863
1-0.2011110.6168611.2698350.9155770.5292441.5749150.9830760.943144-0.9157021.1100590.267902
20.8845731.2864231.7631930.9832101.554588-0.066275-1.1857761.351016-0.5409480.059014-0.312408
31.1235491.5305231.9021281.0014392.181501-0.283498-0.5321310.151330-0.198190-1.2248751.684942
40.8853090.525285-0.092551-0.045502-0.110581-1.058250-1.439472-1.292743-0.035914-0.818917-1.987513
5-1.188030-0.989523-0.894702-0.464608-0.876067-0.5186020.3599130.9763970.393456-1.3471850.122527
60.2525500.7455561.2398500.4953030.7540920.274515-0.4778880.893359-0.518612-1.094333-0.734510
7-0.0782870.424146-0.404042-1.269949-0.4724682.8036571.7551530.502194-0.3021821.625957-0.845243
8-0.705991-0.897418-0.848077-0.925737-0.6029610.125781-0.1227800.545166-0.8517080.6033480.303450
91.1057941.6602361.1095780.2503540.869489-0.236813-0.896503-0.319711-1.0363591.4187030.586520

Last rows

oz1oz2oz3oz4oz5oz6oz7oz8oz9oz10target
2400.227709-0.5531070.1442790.7979170.001782-0.978418-1.452502-0.6043910.552947-1.2314821.177342
2410.2938031.0131261.253632-0.0613940.754829-0.233564-0.5720650.686550-1.274902-0.694388-1.701008
2421.4963890.9116871.3025940.8994881.957655-1.1287160.240684-1.6516730.809792-1.6019070.166224
243-1.664012-1.305592-0.5707950.597441-0.4416190.4446471.252585-1.5701620.778465-0.1559730.014270
244-0.262266-0.5846220.1854571.521376-0.230752-0.791987-1.0444121.056330-0.861209-0.7825171.228233
245-0.4233170.401348-0.690589-1.549696-0.623756-1.389366-0.148829-1.6453340.461814-1.184203-0.184222
2460.8509060.774398-1.574854-1.552231-1.447952-1.304189-1.5139571.2115140.6748050.976286-2.484710
2471.9097141.1542610.6650720.3683521.237317-0.534115-0.756593-1.386420-1.417617-0.6341791.020654
2481.1503261.0008220.8184800.0297160.9982030.203011-0.239069-0.5076081.6843041.406528-1.157108
249-0.0704160.211868-0.1202600.115081-0.1833890.4763330.0046500.8134670.7067860.7804370.234165